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February 27, 2007
Business Intelligence networking in China
I was enthusiastic to see Shawn’s announcement last week that, with Spring approaching, BeyeNETWORK is sprouting new global sites, especially a new portal for China: BeyeNETWORK.cn . Over the last couple of years I have been lucky to be more involved in the Chinese market. There are remarkable prospects there for BI as enterprises develop and mature through business cycles at an astounding rate. However, there are also unique social and cultural differences in the business world that western BI specialists may overlook. The challenge is how to succeed with BI in China with the best technology and practices, without compromising these unique needs.
Meeting this challenge will need a blend of experienced specialists (inevitably trained at first in the established IT world of western commerce), and insightful local entrepreneurs. Fortunately, the BI world is remarkably open and welcoming of new ideas; and local BI vendors in China are specially dynamic and innovative. I have high hopes that BeyeNETWORK.cn can capture that interaction live on the web.
As it happens, I had the opportunity to meet with one of these dynamic BI companies, almost immediately after Shawn’s announcement when I returned from TDWI. Frank Fu from the BI team at U-Soft demonstrated their latest Aurora BI Server. Aurora integrates with SQL Server Analysis Services, and provides a full front-end for business decision makers to browse KPIs and reports in a very interactive manner. For example, in addition to seeing a timeline graph in the dashboard, a user could add various trendlines in the front-end.
Typically, when looking at end-user BI for the western market we think of this analytic functionality as ideally being on every desktop. Frank pointed out to me that in the case of some U-Soft customers, very few end-users (typically only most senior management or officials) might actually use the end user tools. This is one of the differences we need to consider – interactive decision making may still be centralized and quite hierarchical, with only more static reports being delivered to a broader audience. Speaking of reports, Aurora easily handles an issue several BI companies have run into in China – the need to deliver standardized reports in a rather complex, and rather inflexible, government format. (It’s tax time here in the US, of course, so we’re in no position to criticize such forms!)
Another area in which local BI vendors in China are expert is interfacing with regionally specialized ERPs: a rapidly growing market serviced by companies such as KingDee and Langchao who have over 55% of the total ERP market. In other words, as the Chinese economy grows (ignore today’s temporary blip on the exchange!) then perhaps we may see these names become as dominant as SAP, Oracle Apps or Dynamics: at the very least expect them to be as familiar as Sage or Lawson.
Now, please don’t get the impression that all Chinese BI is highly specialized and locally focused. There are BI practices in China which are already delivering great results locally and to US enterprises. A great example is Minesage, where my friend Dachuan Yang’s team not only implement excellent practices for the Chinese market – they also build some beautiful and innovative front-ends for cutting-edge uses, such as predictive analytics, segmentation and cluster analyses for the Microsoft adCenter online advertising platform.
So I do wish the BeyeNetwork team great success in launching their Chinese portal. It’s certainly a market that we in the BI world cannot ignore, and have much to learn from.
再见!
Posted by Donald Farmer at 10:47 PM | Comments (1)
February 19, 2007
Predictive Analytics for the Excel user ... and that means for you.
I was speaking at a BI event in Ireland a couple of weeks ago. After one session, one of our partners decided to collar me with some friendly criticism of Microsoft's well-known slogan BI for the masses. "You can have all the dashboards and reports you want," he said, "But until I can open up Excel and do cutting-edge analysis right there, it's all just blowing smoke. Excel is where I do my work, and that is where my BI needs to live to be efficient. It is all well and good having data mining or some such on the server, but it’s too complex. I need it in Excel, and I can't wait for that day to arrive." I could feel, every time he stressed Excel that he was mentally prodding me, with good humour I must say, until I got the point.
I hope I did not look smug - but forgive me if I did. For the answer was simply, "You only have to wait a week or so. SP2 of SQL Server 2005 has exactly what you need." At the next session, I specifically demonstrated the data mining features. We took a table of customer sales data in Excel. With a few clicks, we had detected categories of customers - base on their demographics in that example. We labeled our rows with these new categories. Detecting outliers based on patterns discovered by the mining add-ins was only a few clicks more. We built predictions of future sales, directly inside Excel. We used goal seeking to find how to move customers from low-value categories to those with a higher potential.
I watched my friendly critic's expression out of the corner of my eye. He was grinning hugely. I wonder if he thought I stayed up all night coding the demo, as it so exactly matched what he asked for.
All these features and many more are in the SQL Server Service Pack 2 released today - February 19th. I believe the Microsoft Data Mining Add-ins for Excel are a real game-changer. They bring the power of predictive analytics to every desktop, along with clustering and segmentation, and some powerful data preparation features. You can read more about the add-ins by following the link, and you can download them freely too.
Why are these features so significant? For years now, business users have too often looked on data mining as cryptic - at worst almost mystical - in its complexity. It was the realm of experts in the backroom, applying intimidating algorithms for the greater benefit of all. This miasma of complexity has hung around largely because it has been so difficult for end users - business analysts mainly - to get their hands dirty with predictive analysis. Until now, specialists served the business user with carefully prepared and presented data mining results that were simply not in the business users’ domain of expertise to criticize. At best they could fall back on the saying of the wonderful Scottish scul?tor George Wyllie who memorably said, "Ye don't need to know how a thing works, to know that it is nae workin'."
I remember when OLAP had the same air of intimidating difficulty. Multi-dimensional hierarchical browsing sounded like something only Doctor Spock could really understand. When Microsoft brought OLAP to the desktop through Pivot Table Services, end users could start to grasp the power of the dimensional modeling method, and to gain some insight into the techniques and capabilities, and limitations, of the technology.
The Data Mining Add-Ins will do the same for predictive analytics. Just as not every analyst rushed off to become a dimensional modeler, I do not expect them to become a data miner either. However, they will learn more about the techniques, will discover their usefulness and limitations, and will respect and trust the technology more because of it. Just as with OLAP, I expect there will be nay-sayers who maintain that there really is something special and arcane about predictive analysis: they'll still be saying that, even as the technology is commoditized on desktops all around them. Because I’ll tell you something else about these Add-Ins, too: they are beautiful to work with.The SQL Server Data Mining team have done a wonderful job with them - the user interfaces are as rich, informative, and nicely crafted as any other Excel feature.
Now, I’m not going to pretend that the Data Mining Add-Ins are a miracle application that somehow can deliver perfect and reliable predictive technology to the inexperienced user. There are still many issues of data preparation, and model validation that we’ll explore in future posts. However, analysts close to the data, and already experienced with BI (as most of readers of this blog will surely be) - such users will love these new tools; and I in turn would be very happy to hear more of your experiences with them.
Posted by Donald Farmer at 7:51 PM | Comments (0)
